Machine learning books are getting hotter and hotter. What will be the future trend?
We live in an era of data explosion. We must rely on computers to understand and use this data, giving the machine intelligence. Letting machines learn to learn is the only way to develop IT technology. Therefore, from a technical point of view, it is not surprising that machine learning books are becoming more and more popular. But the question is, what will be the future trend of machine learning books? Is this kind of anger a kind of virtual fire?
How to learn the machineMachine learning is the core of artificial intelligence. It is the fundamental way to make computers intelligent. Its application spans all fields of artificial intelligence. It mainly uses induction, synthesis rather than deduction. Having said that, we have to say that the current machine is not just on the desktop. On the mobile side, a variety of handheld devices are becoming more and more sophisticated, and a variety of wearable devices are emerging.
In fact, the expansion of smart devices is only in its infancy. Mobile devices are currently surpassing desktop devices in terms of shipments, and we have doubled the number of smart devices if we look at it. After the wearable device landed, there was an explosion of the Internet of Things and the Internet of Things. And as the number of smart devices continues to grow, how to make smart devices more artificial intelligence becomes a big problem.
At present, the most contacted us may be Apple's Siri software. Siri is an Apple voice function software, only available in the latest Apple iPhone4S. Simply put, Siri is a voice control function of Apple's iPhone4S. Siri can transform iPhone4S into a "talking smartphone". You are now Let it help you make calls, read text messages, check the weather, set up meeting schedules, and more. With Siri software, Apple's mobile phone is no longer just a cold machine, but a smart assistant to the owner. With it, it is equivalent to a smart small robot that can realize the interaction between the user and the smart phone. With the release of the Chinese version of the IOS6 system Siri, we can experience the interaction with the iPhone and the Chinese in the future, which will bring life to life. More fun.
While Siri is popular with users, more and more companies are beginning to focus on introducing Siri-like features into their products. Such as Microsoft's Cortana voice assistant, BlackBerry voice, and Syabette Concier, a Japanese competitor who successfully defeated Siri in the Japanese market. In addition, although GoogleNow claims to be able to work with Siri, it is actually still being used as a competitor to Siri.
The popularity of the Siri-like application is just a portrayal of the widespread use of machine learning. Although the application of machine learning classes is getting more and more attention, it is never an easy task to implement it. Machine learning is a multi-disciplinary subject involving many disciplines such as probability theory, statistics, approximation theory, convex analysis, and algorithm complexity theory. It specializes in how computers simulate or implement human learning behaviors to acquire new knowledge or skills and reorganize existing knowledge structures to continuously improve their performance. This determines that it is still an evolving technology.
Machine learning plays an important role in the research of artificial intelligence. An intelligent system without learning ability is hardly a true intelligent system, but the past intelligent systems generally lack the ability to learn. For example, they cannot self-correct when they encounter an error; they do not improve their performance through experience; they do not automatically acquire and discover the knowledge they need. Their reasoning is limited to deduction and lack of induction, so at most it can only prove that there are facts and theorems, but not new theorems, laws and rules. With the in-depth development of artificial intelligence, these limitations have become more prominent. It is in this situation that machine learning has gradually become one of the core of artificial intelligence research.
From the perspective of the big environment, in the context of today's big data era, capturing data and extracting valuable information or patterns from it has become a decisive means for all industries to survive and seek development, which makes this past an analyst and mathematician. The exclusive research field is getting more and more attention.
Therefore, from the perspective of the development prospects of the smart device itself and the data itself, the prospect of machine learning is very bright.
The weakness of machine learning booksMachine learning books have begun to take shape. However, compared with the application prospects of machine learning, there are still many fatal weaknesses in current machine learning books. But these weaknesses can also be transformed into bursts and breakthroughs in new books on machine learning.
At present, the research work in the field of machine learning mainly focuses on three aspects: task-oriented research, cognitive model and theoretical analysis. At present, domestic machine learning books are mainly based on theoretical analysis books. Therefore, once individual combat books are launched, they are generally welcomed by readers. For example, the popular "Turing Programming Series: Machine Learning" is not only about theory, but also uses Python to analyze mainstream machine learning algorithms, k-nearest neighbor algorithm, naive Bayesian algorithm, LogisTIc regression algorithm, support vector machine, AdaBoost integration method, tree-based regression algorithm and classification regression tree (CART) algorithm. Therefore, the introduction of machine learning books in China can not only lead it to the direction of the curriculum in colleges and universities, but only the classics and not the actual combat.
In addition, planners must note that machine learning books must be a rapidly improving variety, and machine learning technology has been around for more than 20 years. It is also a young discipline, and the role of the environment has brought it into a period of revival. In this way, new technologies related to it will continue to emerge.
Going back to the question we started, maybe we can end it with a scene conversation - the wife turned to ask her husband: "Dear, what is machine learning?" The husband replied: "T-800 Terminator." That is T- The reverse model project of 800 artificial intelligence technology. If we think of the T-800 Terminator as machine learning, this understanding will definitely be biased, but let us think about the power of the T-800 Terminator! It is the future of machine learning.
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